DBMS > IRONdb vs. Microsoft SQL Server vs. SAP Adaptive Server vs. VoltDB

System Properties Comparison IRONdb vs. Microsoft SQL Server vs. SAP Adaptive Server vs. VoltDB

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Microsofts flagship relational DBMS

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

with Boeing's Spatial Query Server

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

www.circonus.com/solutions/time-series-database/

www.microsoft.com/en-us/sql-server

www.sap.com/products/technology-platform/sybase-ase.html

www.voltdb.com

Technical documentation

docs.circonus.com/irondb/category/getting-started

learn.microsoft.com/en-US/sql/sql-server

help.sap.com/docs/SAP_ASE

docs.voltdb.com

Developer

Circonus LLC.

Microsoft

SAP, Sybase

VoltDB Inc.

Initial release

2017

1989

1987

2010

Current release

V0.10.20, January 2018

SQL Server 2022, November 2022

16.0

11.3, April 2022

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

C++

C and C++

Java, C++

Server operating systems

Linux

Linux
Windows

AIX
HP-UX
Linux
Solaris
Unix
Windows

Linux
OS X

for development

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

only a subset of SQL 99

APIs and other access methods

HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C++
Cobol
Java
Java
Perl
PHP
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes, in Lua

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Java and Transact-SQL

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic, metric affinity per node

tables can be distributed across several files (horizontal partitioning); sharding through federation

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

configurable replication factor, datacenter aware

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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